Temporal voxel data structure

ABSTRACT

Systems and methods can be used to store data in a temporal voxel buffer. A first voxel array is stored in association with a first voxel in a voxel grid. The first voxel array includes a plurality of time values. A parameter value is stored in association with each time value of the first voxel array. A second voxel array is stored in association with a second voxel in the voxel grid. The second voxel array stores at least one time value. At least one parameter value is stored in association with the at least one time value of the second voxel array. At least one of the time values stored in the first voxel array is different from each of the at least one time value included in the second voxel array.

BACKGROUND

The present disclosure generally relates to computer animation, and morespecifically to motion blur simulation.

When a camera is used to create an image of a moving object, the objectmay appear blurred due to the motion of the object during the time overwhich the camera shutter is open to capture an image. Similarly, anobject may appear blurred in a single frame of a movie recorded by acamera due to movement of the object while the frame was captured.“Motion blur” describes the blurred appearance of moving objects orother image components in a frame. In computer animation, motion blurmay be simulated so that image components in motion have a blurredappearance similar to that produced when a moving object is imaged by acamera.

One existing approach to simulating motion blur is a smearing technique,which involves distributing a density value for a given voxel acrossvoxels that overlap with the path of a motion vector for the givenvoxel. However, smearing can result in various problems, such as lostshading detail. Another approach involves introducing motion blur duringrendering. For example, a motion vector can be assigned to each samplepoint of a lattice representing a volume to be rendered. The lattice isdeformed according to the motion vectors, and when sampling values alongrays through the lattice, a motion blur effect results from samplingrandomly in time. However, storing vector-based motion informationassociated with each sample point can be computationally expensive atrender time.

Therefore, it is desirable to provide new systems and methods foraddressing such problems associated with simulating motion blur.

BRIEF SUMMARY

Embodiments can provide systems and methods for providing simulatedmotion blur in the computer animation of animated scenes. A first voxelarray associated with a first voxel in a voxel grid of athree-dimensional model can be stored in memory by a processor. Thefirst voxel array can include a plurality of time values. The firstvoxel array may include, for each time value, a parameter value of aparameter of an animated scene associated with the first voxel at thetime value. A second voxel array associated with a second voxel in thevoxel grid can also be stored in a memory by a processor. The secondvoxel array can include at least one time value. The second array mayinclude, for the at least one time value, a parameter value of aparameter of the animated scene associated with the second voxel. Atleast one of the time values stored in the first voxel array may bedifferent from each of the at least one time value included in thesecond voxel array.

Other embodiments are directed to systems, devices, and computerreadable media associated with methods described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram showing an illustrative scene in which a prior artvector-based approach to motion blur simulation is used.

FIGS. 2A-2B are diagrams illustrating microvoxel lattice deformationaccording to a prior art vector-based approach to motion blursimulation.

FIG. 3 is a diagram showing an illustrative scene in which a voxel gridmay be used, in accordance with an embodiment.

FIGS. 4A-4B are diagrams illustrating data associated with voxels of avoxel grid, according to an embodiment.

FIG. 5 is an illustrative diagram of a temporal voxel buffer datastructure, according to an embodiment.

FIG. 6 is a flowchart for storing information in a temporal voxelbuffer, according to an embodiment.

FIG. 7 is a flowchart for generating voxel buffer data to be stored in atemporal voxel buffer, according to an embodiment.

FIG. 8 is a flowchart for generating a microvoxel lattice, according toan embodiment.

FIG. 9A shows an illustrative microvoxel lattice relative to a voxelgrid, according to an embodiment.

FIG. 9B shows illustrative sample positions within a voxel, according toan embodiment.

FIGS. 10A-10B show an input primitive relative to a voxel subgrid,according to an embodiment.

FIG. 11 is a diagram showing illustrative rays cast through a volume foruse in rendering.

FIG. 12 is a flowchart for rendering an image using a temporal voxelbuffer.

FIG. 13 is a simplified block diagram of a system for creating computergraphics imagery (CGI) and computer-aided animation that may implementor incorporate various embodiments.

FIG. 14 is a block diagram of a computer system or informationprocessing device that may incorporate an embodiment, be incorporatedinto an embodiment, or be used to practice any of the innovations,embodiments, and/or examples found within this disclosure.

DEFINITIONS

An animated scene is a series of images (frames) as seen by a virtualmovie camera (render camera) in a three-dimensional animated world. Theframes are effectively obtained at successive times, e.g., as would bedone for a physical camera. Rendering is the process for creating eachimage from the three-dimensional (3D) animated world and a currentconfiguration of the virtual camera, e.g., using geometric and/ormathematical descriptions of objects in the 3D world.

A voxel is a volumetric element of a three-dimensional object to berendered. The voxel may be identified by coordinates corresponding tothe location of the voxel in space, such as three coordinates indicationthe position of the voxel in 3D space. Data indicating the appearance ofthe voxel, such as opacity, color, etc., may be stored in associationwith the voxel coordinates. The three-dimensional object may be anamorphous object, such as steam. For animation, an object may berepresented as a set of voxels. Information related to the appearance ofthe object may be stored in association with each voxel of an object.

A temporal voxel buffer is a data structure that stores data inassociation with each voxel of voxel grid. The data associated with avoxel may be an array (i.e., a “voxel array”) stored in computer memory.Each element of a voxel array may be one or more parameter valuesassociated with a time value. A voxel array may store a time value inaddition to the one or more parameter values for each array element. Avoxel grid may be an orthogonal grid with evenly spaced congruentvoxels. A subset of the voxels of the voxel grid may be referred to as avoxel subgrid.

A primitive is used to indicate the shape of an object. Primitives caninclude zero-dimensional, one-dimensional, two-dimensional andthree-dimensional primitives, such as volumetric primitives, geometricprimitives, and voxel buffers. A geometric primitive may be a point, acurve, a polygon, a surface, or other geometric object. A volumetricprimitive may be a sphere, cylinder, rectangular prism, or othergeometric volume.

A sampling lattice corresponds to a set of vertices associated with anobject The sampling lattice may be used for rendering the object. Forexample, the vertices of a lattice may be used to determine howdifferent points on the surface of the object should be shaded given thecurrent configuration of the render camera. The number of vertices in alattice corresponds to a resolution of the lattice, where more verticescorrespond to a higher resolution. The vertices of the lattice maydefine polygons. The resolution of the object may change based ondistance of the object from the render camera. The polygons at any givenresolution can form a tessellation pattern. Different areas of an objectmay have different tessellation patterns (example of a lattice), suchthat different areas are represented with different resolutions. In someembodiments, a sampling lattice may be a microvoxel lattice. Where theterm “microvoxel lattice” occurs below, it will be understood that anysampling lattice may be used.

The term “random” as used herein can refer to values obtained using arandom number generator. Where a value is described as being random, itwill be understood that pseudorandom values or multiple values may beused in lieu of random values.

DETAILED DESCRIPTION

Embodiments are directed to generating, storing and rendering temporalvoxel data. A temporal voxel buffer is a data structure for storingparameter values in association with each voxel of a voxel grid. Thevoxel buffer may store parameter values and associated time values invoxel arrays. The change in parameters over time represents the changein the appearance of the voxel over time. The appearance of motion blurof an object represented by the voxel grid may be simulated using thechange in the appearance of the voxels over time, as stored in the dataof the temporal voxel buffer.

To populate a voxel grid data structure, the appearance of an object maybe sampled at various times and locations. The shape of an object may berepresented by one or more primitives, such as geometric shapes. Amicrovoxel lattice can be generated from the one or more primitives anda shader can be applied to the vertices of the microvoxel lattice.Whereas the microvoxel lattice may have an irregular shape, the voxelgrid is typically an orthogonal arrangement of voxels. The voxel gridmay overlap the microvoxel lattice, such that data sampled from themicrovoxel lattice can be stored in association with voxels havingreadily determinable locations within the voxel grid. Parameter valuessuch as density, color, etc., can be sampled at multiple times andmultiple positions within the voxel grid (e.g., random times and randompositions). The sampled parameter values and times may be stored inassociation with the voxels of the voxel grid. By using the storedvalues sampled from the microvoxel lattice at multiple times andmultiple positions, a renderer can produce an image with a simulatedeffect of motion blur.

An animated scene may be rendered using one or more temporal voxelbuffers. An object having an associated temporal voxel buffer may beamong many objects to be rendered in a scene. For each pixel of therendered image, a value of the pixel can be determined by casting raysthrough the volume. Raymarching is performed along the rays to obtain avalue for a parameter associated with each ray. The parameter values forthe plurality of rays associated with a pixel may be used to obtain thepixel value.

I. Introduction

FIGS. 1 and 3 together provide an example of a scene in which simulatedmotion blur may be desirable. The animated scene illustrated in FIGS. 1and 3 includes steam hovering over a coffee cup. If the water particlesof the steam move over the duration of a single “frame” of the animatedscene, it may be desirable to show the particle with motion blur.Additionally, if the cup is moved, or if the background moves relativeto the cup, it may be desirable to simulate motion blur for the motionof these image components.

Various data structures may be used to represent the shape andappearance of the objects in an image. Two approaches to data forrepresenting changes in an image component over time are describedbelow.

A. Prior Art Approach: Simulating Motion Blur using Motion Vectors

A prior technique to simulating motion blur involves associating motionvectors with vertices of a microvoxel lattice to indicate the motion ofan object over time. A microvoxel lattice may be a three-dimensionalarrangement of vertices representing the shape of an object. In avector-based approach to motion blur simulation, each vertex of amicrovoxel lattice may have an associated vector defining the motion ofthe vertex over time. At render time, the vertices of the lattice may besampled at multiple times (e.g., randomly in time). The memory overheadof this approach is high, because the position of each vertex as itchanges over time must be determined according to the vector associatedwith motion of each sample point.

FIG. 1 is a diagram showing an illustrative scene in which a prior artvector-based approach to motion blur simulation is used. In theillustrative example of FIG. 1, a coffee cup 102 and steam 104 are beingcaptured from the perspective of virtual camera 106 to create ananimated scene. Microvoxel lattice 108 can be used to represent theappearance of steam 104, such as the shape of the surface of a cloud ofsteam 104. Microvoxel lattice 108 includes vertices 110. It may bedesirable to animate the motion of steam 104 using motion blurtechniques. Vectors associated with the voxels can be used to indicatethe motion of microvoxel lattice 108 over time.

FIGS. 2A-2B are diagrams illustrating microvoxel lattice deformationaccording to a prior art vector-based approach to motion blursimulation. FIG. 2A shows a first state of a microvoxel lattice 108 andFIG. 2B shows a second state of the microvoxel lattice 108. For example,FIG. 2A may show the state of microvoxel lattice 108 at time t=0 andFIG. 2B may show the state of microvoxel lattice 110 at time t=1. Eachvertex 110 of microvoxel lattice 108 has an associated vector 202, e.g.,defining the movement of vertex 108 from t=0 to t=1. One or moreparameters to define the appearance of the microvoxel lattice may beassociated with each vertex 108. For example, a density value may bestored in association with each vertex. By sampling the values of theparameters associated with vertices 110 of microvoxel lattice 108 atmultiple times between t=0 and t=1 (e.g., at random times between t=0and t=1), the appearance of motion blur for an object associated withmicrovoxel lattice 108 may be simulated. The blur results from thechanging shape of microvoxel lattice 110.

B. Simulating Motion Blur Using Temporal Voxel Buffer

As indicated above, motion blur may be simulated based on the variationin parameter values over time. The prior art approach described abovedetermines variations using information about the motion of vertices 110of microvoxel lattice 108. The temporal voxel buffer approach cansimulate motion blur with stored information about how parameter valueschange over time, without requiring information about how a microvoxellattice moves over time to be used at render time. Because the temporalvoxel buffer can store predetermined values associated with a set oftimes for each voxel of a voxel grid, using a temporal voxel buffer formotion blur simulation places lower demands on processing and memorycompared with prior art approaches. Additionally, the voxel gridtypically has an orthogonal structure of congruent voxels, so the valuesof voxels within the voxel grid is more easily determined compared withthe values of the moving vertices of a microvoxel lattice.

FIG. 3 is a diagram showing an illustrative scene in which a voxel grid300 may be used, in accordance with an embodiment. Voxel grid 300includes voxels 302. In the illustrative example of FIG. 1, coffee cup102 and steam 104 are being captured from the perspective of virtualcamera 106 to create an animated scene. Information about the appearanceof the steam may be stored in association with voxels 302 of voxel grid300. The information may include one or more parameters (e.g., density,color) associated with a time value. For example, for a particular voxel402 (see FIG. 4), a series of density values may be stored correspondingto time values between time t=0 and t=1, where one frame of the animatedscene is to be rendered at time t=0, and the next frame of the animatedscene is to be rendered at t=1. The series of density values indicatehow the density appearance of the voxel changes between t=0 and t=1. Theinformation may be stored in computer memory using a temporal voxel datastructure. In the illustrative example of FIG. 3, the temporal voxelbuffer can be used to animate the motion of steam 106 using motion blurtechniques.

II. The Temporal Voxel Buffer Data Structure

The temporal voxel buffer stores information about the change inappearance over time of an object, surface, or any other component of ananimated scene. For example, a temporal voxel buffer can storeinformation in association with voxels 302 of voxel grid 300 about howthe appearance of steam 106 changes over time.

The temporal voxel buffer data structure may store information inassociation with a plurality of voxels. In some embodiments, thetemporal voxel buffer data structure stores at least one array inassociation with each voxel of a voxel grid. The temporal voxel bufferdata structure may additionally store an array of offset values (e.g.,location in memory of data) for indicating the location of dataassociated with each voxel in storage (e.g., in storage in a functiontable). The temporal voxel data struture may be a tree, such as asingle-level tree that stores data for groups of voxels. It will berecognized that alternative data structures may be used for storingvoxel data in association with voxels of a voxel grid.

A. Voxel Data Compression

The data stored in the temporal voxel buffer can correspond to a changein a parameter (or in multiple parameters) over the time duration of asingle frame of an animated sequence. A second temporal voxel buffer canbe used to store data corresponding to a subsequent frame of theanimated sequence, and so on. In some embodiments, data may be stored inassociation with a voxel for a time duration that is less than orgreater to one frame.

When the variance in the appearance of a voxel is large, relatively moredata points may need to be stored in the voxel array for the voxel. Whenthe variance is small, fewer data points may be needed. A compressionalgorithm may be applied to the data points associated with a particularvoxel so that a compressed representation of the data may be stored forthe voxel.

FIG. 4A is a diagram to illustrate uncompressed data associated withvoxels of a voxel grid, according to an embodiment. The temporal voxelbuffer stores data associated with each voxel 302 of voxel grid 300.

Graphs 402 a-410 a are illustrative examples of data that may be storedin association with voxels 302. Each graph 402 a-410 a shows the changein a density value over time for a particular voxel. For example, graph402 a shows the change in a density value for the voxel indicated at402.

FIG. 4B is a diagram to illustrate compressed data associated withvoxels of a voxel grid, according to an embodiment. Graphs 402 b-410 bare illustrative examples of compressed data that may be stored inassociation with voxels 302.

Compression may be applied to the data illustrated at 402 a-410 b ofFIG. 4A to produce reduced data sets shown in the graphs illustrated at402 b-410 b of FIG. 4B. For example, some of the graphs 402 a-410 acontain redundant data, e.g., graph 404 a has the same density value atthe last three data points of the graph. Because there is no variationin the appearance of the voxel between the last three data points, itmay not be necessary to store a parameter value at each of these timeintervals. The data of graph 404 a may be compressed to obtain the datashown in graph 404 b. For example, a compression algorithm may beapplied to the data set shown in graph 404 a to obtain a compressed dataset shown in graph 404 b. In this way, the amount of data stored inassociation with voxels 302 of voxel grid 300 may be reduced.

As another example, the data points of graph 410 a are located along aline with a constant slope. It may not be necessary to store each ofdata points of 410 a, as parameters at intermediate points along theline can be interpolated from data at the end points. Accordingly, thedata of 410 may be compressed such that only the two points shown at 410b are stored.

Any compression algorithm may be used to reduce the amount of datastored in association with voxels 302. For example, lossy compression,spline-based compression, or other compression techniques may be used.

B. Voxel Arrays of the Voxel Buffer Data Structure

FIG. 5 is an illustrative diagram of a temporal voxel buffer datastructure 500 according to an embodiment. In. FIG. 5, the illustrativegraphs 402 b-410 b of FIG. 4B are shown as voxel arrays 502-510.Temporal voxel buffer 500 includes one or more voxel arrays 502. Asshown, temporal voxel buffer 500 corresponds to a change in a parametervalue for a voxel grid during a frame of an animated scene.

As an example, temporal voxel buffer 500 may be a single-level tree thatstores each voxel 302 of voxel grid 300. A voxel array 502 may be storedin association with each voxel 302 of voxel grid 300. If the appearanceof a voxel does not change over time (e.g., over the duration of aframe), the block may store no data for the voxel, or a single parametervalue may be stored for the voxel. For example, voxel array 508 stores asingle parameter value, as the density value for this voxel does notchange over the time period of the voxel buffer.

In some embodiments, the temporal voxel buffer may store an array ofoffset values in association with each voxel 302 of voxel grid 300. Thearray of offset values may indicate the location in memory of one ormore parameter and/or time values for a voxel.

Voxel array 502 may be an array of one or more values stored in computermemory. A voxel array may be stored in association with voxel 402. Forexample, voxel buffer data structure 500 may store one or more valuesidentifying a voxel 402 as corresponding to a stored voxel array 502, asmay be done via a table. Alternatively, voxel array 502 may storeinformation identifying a voxel, e.g., voxel array 502 may include avoxel identifier at the beginning or end of the data values. In someembodiments, a voxel 402 associated with a voxel array 502 can beidentified based on the way in which voxel array 502 is stored in voxelbuffer data structure 500, such as the location of voxel array 502within voxel buffer data structure 500. For example, the voxels may bedefined to have a particular order, and the corresponding voxel arrayscan be stored in that same order. Any suitable indication of thebeginning and end of a voxel array can be used to signify when the datacorresponds to a new voxel.

Voxel array 502 can store one or more parameter values associated with avoxel 402. A parameter may be a characteristic of a voxel, such as adensity, color, opacity, temperature, attenuation coefficient for awavelength of light, etc. As indicated at graphs 402-410, the value of aparameter may vary over time for a voxel during a frame of an animatedscene. Voxel array 502 can be used to store the change in a parameter,such as density, over the time of a frame for a particular voxel.

In some embodiments, voxel array 502 may be an associative array. Forexample, as shown in FIG. 5, voxel array 502 may store value pairsincluding a density value and a time value. Element 512 of array 502corresponds to the last data point on graph 402, indicating that thedensity of voxel 302 has a magnitude value of 8 at time t=0.8.

Although the illustrative voxel arrays 502-510 of FIG. 5 are shownstoring value pairs, it will be recognized that alternative voxel arraystructures may be used. For example, a voxel array 502 may not storetime values in the elements of the array. If the voxel array does notstore time values, the time value associated with an element may bedetermined based on, e.g., the location of the element within the array.

In some embodiments, multiple parameter values may be stored in eachelement of voxel array 502. For example, a density value, a color value,and a time value could be stored in each element of the array. Inanother embodiment, a voxel array may be a multidimensional array. Forexample, density values for a voxel 402 can be stored in a first row ofa multidimensional array and time values associated with the densityvalues can be stored in a second row of the multidimensional array.Additional parameter values may be stored in additional rows of themultidimensional array.

Voxel arrays may be nested within other arrays. For example, a voxelarray could be nested within a voxel grid array for all voxels 302 ofvoxel grid 300. Data associated with a voxel 402 could be accessed byreading a voxel array from coordinates of the voxel grid arraycorresponding to coordinates of a voxel 402 within voxel grid 300.

Multiple arrays may be stored in association with each voxel 302. Forexample, where a set of parameters is available (e.g., sampledtime/density value pairs), an array may be stored in association with avoxel indicating the offset within the set of parameters to the firstparameter value (e.g., first time/density pair) for the voxel. Multiplearrays may be used to store parameter values for different parameters.For example, a density array, such as density array 502 may be stored inassociation with voxel 402, and a color array could also be stored inassociation with voxel 402, the color array indicating the change incolor values over time for voxel 402.

As shown in temporal voxel buffer 500, voxel arrays 502-510 may storeparameter values corresponding to a time range, e.g., from time t=0 tot=1. Although the illustrative voxel buffer 500 includes arrays with upto six time steps in the range t=0 to t=1, it will be recognized thatother numbers of time steps may be used, such as 10 time steps over therange t=0 to t=1. The time duration of the voxel array may be related tothe duration of a single frame. For example, if a frame has a durationof 1 unit of time (e.g., 1 unit of time could be equal to 1/60^(th) of asecond, 1/24^(th) of a second, 1 second, or any other length of time),the voxel array may indicate changes in density from time t=0 to t=1. Inother embodiments, the time duration of the voxel array may be shorteror longer than the duration of a frame. A second temporal voxel buffermay be used to store voxel arrays for each voxel in a time frame t=1 tot=2, and so on. Although a voxel array time range t=0 to t=1 is used forsimplicity of presentation, it will be recognized that a time range t=0to t=41.6 milliseconds or any other time range can be used for voxelarrays 502.

Voxel arrays may store parameter values at intervals of time over therange of time associated with voxels. For example, voxel array 502stores a density value of 7 in association with time t=0.0, a densityvalue of 0 in association with t=0.2, a density value of 9 inassociation with t=0.4, and so on, such that parameter values are storedat periodic intervals from t=0 to t=0.8.

Voxel array sizes may vary within a temporal voxel buffer 500. Forexample, as shown in FIG. 5, voxel array 510 has fewer elements thanvoxel array 502. Voxel array 510 corresponds to graph 408 b, which is acompressed version of graph 408 a. After data associated with a voxel ofa voxel grid is sampled, e.g. to obtain the data illustrated in graph408 a, compression may be applied to the sampled data to obtain acompressed data set, as illustrated at graph 408 b. In this way, theamount of data to be stored in voxel grid 502 may be reduced. In someembodiments, a compression algorithm may be applied to the parameterdata associated with the voxels 302 of voxel grid 300 to reduce theamount of data stored by voxel arrays 502 of temporal voxel buffer 500.

As shown in FIG. 5, the distribution of time values may vary from onevoxel array to another. For example, voxel array 506 has a distributionof time values including t=0.0, t=0.2, t=0.4 and t=0.8. Voxel array 510has a distribution of time values including t=0.0 and t=1.0. Thedistribution of time values in voxel array 506 is different from thedistribution of time values in voxel array 510. For example, time valuet=0.2 is present in voxel array 506, but time value t=0.2 is not presentin voxel array 510. In other words, voxel array 506 contains at leastone value (t=0.2) that is different from each of the time values ofvoxel array 510.

C. Method

FIG. 6 is a flowchart for storing information in a temporal voxel buffer500, according to an embodiment.

At operation 602, set of voxels 302, e.g., voxel grid 300, may be storedin computer memory. The voxel grid may be used to store data about theappearance of a component of an animated scene, such as an object in thescene (e.g., steam 104.)

At operation 604, a voxel array 502 may be generated for a voxel 402.For example, one or more parameter values may be sampled at a multiplepoints of time and at multiple positions within the voxel. The sampledvalues may be stored in association with the sample times in voxelarrays 502.

At operation 606, voxel array 502 may be stored in association withvoxel 402.

At decision diamond 608, it may be determined whether voxel arrays havebeen generated for all voxels 302 in the set of voxels. If voxel arrayshave not been stored for all of the voxels, a current voxel value may beiterated, as indicated at operation 610. A voxel array can then begenerated and stored for the iterated voxel value, as indicated atoperations 604-606.

At operation 612, volume ray marching may be performed for voxel grid300 to obtain parameter values used in determining the value of eachpixel of an image to be rendered. For example, for each pixel of animage, multiple rays may be cast such that the rays intersect the pixeland voxel grid 300. Each ray may have an associated time value. The timevalues may be random, and the point at which the ray enters voxel grid300 may be random. The value of a parameter (or of multiple parameters,when multiple parameters are stored in association with a voxel) may bedetermined for each voxel along the ray at the time associated with theray. The parameter values for the voxels along the ray may be combinedusing a rendering equation (e.g, composited) for each ray and an averagevalue may be determined for the multiple rays. The average value may beassigned to the pixel, and the process may be repeated for each pixel ofan image. The rendering process is described in more detail below.

At operation 614, an image may be rendered from the sample data forvoxel grid 300. The value acquired as a result of operation 612 may beassigned to a pixel of an image. When values have been obtained for allof the pixels of an image, the image may be rendered according to thedetermined pixel values.

At operation 616, the image rendered at operation 614 may be stored,e.g., in computer memory, as a frame of an animated sequence. Ananimated sequence can be compiled from a series of stored renderedimages.

In some embodiments, the data stored in temporal voxel buffer 500 may begenerated using a rendering process, as described further below.

III. Generating Temporal Voxel Buffer Data

During a frame, the motion of an object can be modeled such that changesin the object can be determined at smaller time steps than the timeinterval between frames. The parameter values and time values associatedwith voxels 302 in temporal voxel buffer may be generated by applying ashader to a microvoxel lattice and sampling values of voxels of a voxelgrid corresponding to the microvoxel lattice. For each voxel, samplesmay be obtained at multiple times and at multiple locations within thevoxel during a frame. For example, a stochastic rasterization techniquemay be used, in which each voxel is sampled at random times and/orrandom locations within the voxel.

A. Method

FIG. 7 is a flowchart of a method 700 for generating voxel buffer datato be stored in a temporal voxel buffer 500, according to an embodiment.Method 700 can be used to generate various voxel arrays of a voxelbuffer. Different settings may be used, which can result in variousvoxel arrays, such as arrays of different length. The data itself canalso result in voxel arrays of different length and time steps. Althoughdescribed with respect to a shader, method 700 can use any routine thatprovides a property of an object.

At operation 702, at least one input primitive is received. The inputprimitive may be received by a software application or other programexecuted by a processor of a computer. In some embodiments, the softwareapplication may be a rendering application.

One or more primitives can be used to represent the shape of an objectto be animated. For example, an input primitive could be a surfaceindicating the shape of steam 104. In another example, an inputprimitive could be volumetric primitive 1002 shown in FIG. 10. In afurther example, an input primitive could be a previously generatedtemporal voxel buffer 500.

At operation 704, a voxel grid 300 may be received at the renderer. Thesize and position of voxel grid 300 may be automatically determined, orthe size and position may be selected such that it partially or fullyoverlaps the area in which motion blur is desired relative to the inputprimitive.

At operation 706, a microvoxel lattice may be generated based on the atleast one input primitive. In some embodiments, a microvoxel lattice maybe generated according to a rendering approach as described in detailwith reference to FIG. 8.

FIG. 9A shows a microvoxel lattice 902 and a voxel grid 300, accordingto an embodiment. Typically, voxel grid 300 partially or fully overlaps,or is coterminous with, microvoxel lattice 902 such that values readfrom the shaded vertices of microvoxel lattice 902 can be stored inassociation with the voxel 402 of voxel grid 300 in which the vertex islocated.

At operation 708 of FIG. 7, a shader may be applied to the vertices ofthe microvoxel lattice. A shader is an algorithm for calculatingparameters that dictate the appearance of an object. For example, theshader could determine a density values for each vertex 904 ofmicrovoxel lattice 902. Using the shader, parameter values may bedetermined at multiple time intervals over the duration of one frame ofan animated sequence.

At operation 710, a variable may be initialized for iteration. Forexample, current voxel value i and sample time/sample position value jmay be set to an initial value (e.g., 1).

At operation 712, multiple sample times and multiple sample positions(e.g., N sample time and N sample positions) are determined for voxel i.The N sample times and/or N sample positions may be determined, forexample, using a random or pseudorandom process, such as a random numbergenerator. For example, each sample time of the N sample times may be arandom sample time in the range t=0 to t=1 for a particular frame of ananimated sequence. Each sample position of the N sample positions may bea random position within voxel i. When the N sample times and N samplepositions are determined, a minimum spacing between the sample timesand/or minimum spacing between the N sample positions may be enforced.

FIG. 9B shows illustrative sample positions 906 within a voxel 402. Forexample, voxel 402 may have 11×11×11 sample points, or 1331 samplepoints throughout the voxel.

The sample points may be arranged in offset rows 908, as shown in FIG.9B. It will be recognized that other numbers and configurations ofsample points could be used. N samples may be acquired for voxel 402, atmultiple sample times and sample positions within voxel 402. Forexample, each of the N samples may be acquired for a random sample timeand at random sample position 906 within voxel 402. In some embodiments,a sample may be acquired at the vertex of the microvoxel lattice that isclosest to the sample point. Alternatively, the sample value may be aninterpolation of the values of two or more lattices that are closest tothe sample point.

In some embodiments, sample positions may be randomly determinedmicrovoxel lattice points within a voxel. Alternatively, samplepositions may be a randomly generated value in the coordinate system ofa particular voxel.

Any number N samples corresponding to a voxel 402 may be acquired, e.g.,16 samples. The number of samples can also be random, potentially with aminimum number specified.

At operation 714, at least one parameter value of microvoxel lattice 902is sampled at sample time j and sample position j within voxel i. Forexample, if vertex 904 is located within voxel i, one or more parametersfrom vertex 904 may be obtained. The parameters associated with thevertices of the microvoxel lattice may change over time, e.g., as themicrovoxel lattice moves according to the motion vectors for itsvertices.

At operation 716, the sample time and the parameter value (or parametervalues) may be stored in memory. For example, a sample time and aparameter value may be stored in a voxel array 502 associated with voxeli.

At decision diamond 718, it is determined whether all of the N sampleshave been acquired, e.g., by determining whether sample value j is lessthan N. If j is less than N, sample value j is iterated, e.g., bysetting j equal to j+1, as indicated at operation 720. If j is equal toN, the voxel array may be compressed, as indicated at optional operation722. Compression of the voxel array of a voxel can result in storage ofvoxel array with fewer elements than the number of samples acquired forthe voxel. For example, a compression algorithm can be applied to the Nsamples acquired for a voxel, such that one or more of the samples aredeleted from the set of N samples acquired for the voxel. Voxel datacompression is described in more detail below.

At decision diamond 724, it is determined whether voxel arrays 502 havebeen determined for all voxels 302 in voxel grid 300, by determiningwhether current voxel value i is equal to the number of voxels in thevoxel grid. If voxels remain for which voxel arrays 502 have not beendetermined, current voxel value i is iterated, e.g., by setting i equalto i+1, as indicated at operation 726. In some embodiments, voxel arraycompression may occur after voxel arrays 502 have been determined forall voxels 302 in voxel grid 300, as indicated at optional operation728. Voxel data compression is described in more detail above.

At A of FIG. 7, a microvoxel lattice 902 may be generated from the inputprimitive according to the operations described with reference to FIG.8.

B. Microvoxel Lattice Generation

FIG. 8 is a flowchart for generating a microvoxel lattice 902, accordingto an embodiment.

At operation 802, voxel grid 300 is divided into voxel subgrids. Voxelsubgrids include a subset of the voxels 302 of voxel grid 300. Anexample of a voxel subgrid is shown at 1004 of FIG. 10A.

At operation 804, current voxel subgrid value i is set to an initialvalue (e.g., 1).

At operation 806, the at least one input primitive (e.g., inputprimitive 1002 shown in FIG. 10A) received at operation 702 is stored toan input primitive buffer. At operation 808, current input primitivevalue j is set to an initial value (e.g., 1).

At decision diamond 810, it is determined whether input primitive jfalls within the bounds of voxel subgrid i. An input primitive may fallwithin the bounds of a voxel subgrid even if the input primitive is onlypartially within the extents of the voxel subgrid. By way of example,referring to FIG. 10A, input primitive 1002 is (partially) locatedwithin the extents of the voxels of voxel subgrid 1004. Accordingly, atoperation 808, it would be determined that input primitive 1002 fallswithin the bounds of voxel subgrid 1004.

At operation 812 of FIG. 8, if input primitive j does not fall withinthe bounds of voxel subgrid j, input primitive j is removed from theinput primitive buffer.

At decision diamond 814, if input primitive j does fall within thebounds of voxel subgrid i, it is determined whether input primitive jexceeds a threshold value. For example, it may be determined whether alength, width, both length and width, or other dimension (or combinationof dimensions) exceeds a distance threshold value, such as a distancespecified in pixels. The threshold value may be a predetermined,automatically determined, or user configurable value of the renderingprogram.

At operation 816, if input primitive j exceeds the threshold value, theinput primitive may be split into two or more subprimitives. Forexample, referring to FIGS. 10A and 10B, input primitive 1002 exceeds athreshold length, and is split into four subprimitives, includingsubprimitive 1006 shown in FIG. 10B. The two or more subprimitives maybe stored to the input primitive buffer, i.e., for further processing.At operation 818, if input primitive j does not exceed the thresholdvalue, input, input primitive j may be removed from the input primitivebuffer.

At decision diamond 820, it is determined whether any input primitivesremain in the input primitive buffer. If input primitives remain in theinput primitive buffer, the current input primitive value j is iterated,as indicated at operation 822, so that the next current input primitivecan be handled at operations 810-818. At operation 824, it is determinedwhether any voxel subgrids remain to be handled, i.e., whether currentvoxel subgrid value i is less than the total number of voxel subgrids.If there are remaining voxel subgrids, the current voxel subgrid value iis iterated, as indicated at operation 826, so that the next voxelsubgrid can be handled at operations 806-820. If there are no remainingvoxel subgrids, i.e., current voxel subgrid value i is equal to thetotal number of voxel subgrids, all subprimitives and all unsplit inputprimitives (i.e., input primitives not split at 814-816) are diced, asindicated at operation 828.

Dicing an input primitive creates a microvoxel lattice 902 from an inputprimitive. For example, dicing may decompose a primitive into smallerpolygons. Many conventional techniques may be used to dice the object,for example, dicing may divide the object into triangles, four-sidedpolygons, and the like. Intersection points of the polygons can form alattice, or the resulting polygons can be considered a lattice. Asexamples, these points can be used for shading and shape representation.The polygons can be smaller than a pixel, and thus may be subpixel-sizedmicropolygons. Each polygon may be tested for visibility and used tomake a pixel (via sampling and filtering steps).

At B of FIG. 8, the flow may proceed to operation 708 of FIG. 7.

C. Advection Approach to Voxel Buffer Generation

In some embodiments, an advection technique may be used to populate atemporal voxel buffer. The advection approach determines parametervalues associated with voxels by sampling values from a fluid simulationfield rather than sampling values from a microvoxel grid. For example,steam 104 may be represented by a fluid simulation field. A voxel grid300 may be generated corresponding to (e.g., containing) the fluidsimulation field. For each voxel 302 of voxel grid 300, a parametervalue may be determined at a sample position and a sample time. In someembodiments, parameter values are determined at multiple samplepositions and multiple sample times. The sample positions and sampletimes may be determined randomly, pseudorandomly, or according toanother process. For example, the sample position may be a randomposition within a voxel, as illustrated at FIG. 9B. Alternatively, thesample position may be a randomly generated value in the coordinatesystem of a particular voxel. In an illustrative example, to determine aparameter value corresponding to a sample time t=0.5, a state could bedetermined for the sample position from the fluid simulation field att=0.3 and at t=0.6. The sample parameter value at t=0.5 can bedetermined based on an interpolation between the parameter values t=0.3and t=0.6. Voxel arrays 502 of temporal voxel buffer 500 may bepopulated applying this advection technique to each voxel at multiplesample times and sample positions within the voxel.

After a temporal voxel buffer is populated, e.g., using one or more ofthe techniques described above, the temporal voxel buffer may be usedfor rendering an image.

IV. Rendering with the Temporal Voxel Buffer

A motion blur effect can be simulated in a process for rendering animage using a temporal voxel buffer data structure. In some embodiments,a raymarching approach to rendering may be used. Rendering withraymarching involves casting rays such that the rays intersect a pixeland the voxel grid corresponding to the temporal voxel buffer. The raysmay be random in time and random in direction. The value of a parameter(or of multiple parameters) of the voxels along the ray at the timeassociated with the ray may be composited along the ray. The parametervalues may be averaged across the multiple rays to generate an averagevalue for the parameter. This value may be used to determine one or morevalues corresponding to a pixel of an image. The image may be a frame ofan animated sequence.

FIG. 11 is a diagram showing illustrative rays cast through a volume foruse in rendering. Ray 1100 is typically one of a plurality of rays(e.g., rays 1100-1104) cast through voxel grid 300. Ray 1100 may bedefined by the location of a pixel of an image to be rendered, and thepoint at which the ray enters voxel grid 300, e.g., entry point 1106. Anillustrative image to be rendered is shown at 1108. Image 1108 includesa plurality of pixels 1110. Rays 1100-1104 correspond to pixel 1110.

A plurality of rays 1100-1104 are cast through voxel grid 300 to arriveat pixel 1110. The multiple rays are cast at multiple times and inmultiple directions. For example, in the illustrative example of FIG.11, ray 1102 is cast at time t=0.2 in a first direction, ray 1104 iscast at time t=1.0 in a second direction, and ray 1106 is cast at timet=0.5 in a third direction. The direction of each ray 1100 and the timeassociated with each ray 1100 may be determined randomly,pseudorandomly, or by another process.

FIG. 12 is a flowchart for rendering an image using a temporal voxelbuffer, according to embodiments of the present invention. To render animage using a temporal voxel buffer, data from the temporal voxel bufferassociated with a voxel grid is read along rays cast through the voxelgrid, as shown in FIG. 11.

At operation 1202, a temporal voxel buffer 500 associated with voxelgrid 300 is received. The temporal voxel buffer 500 may be received by asoftware application, such as a rendering application. At operation1206, current ray value r is set to an initial value and current pixelvalue p is set to an initial value.

At operation 1206, multiple sample times and multiple sample position(e.g., N sample times and N sample positions of entry into a voxel grid)are determined for pixel p. The N sample times and N sample positionsmay be determined, for example, using a random or pseudorandom process,such as a random number generator. For example, each sample time of theN sample times may be a random sample time in the range t=0 to t=1 for aparticular frame of an animated sequence. Each sample position of the Nsample positions may be an entry point (e.g., 1106) of voxel grid 300.Any number N samples may be acquired in this manner. When the N sampletimes and N sample positions are determined, a minimum spacing betweenthe sample times and/or minimum spacing between the N sample positionsmay be enforced.

At operation 1208, current ray r (e.g., ray 1100) is cast through voxelgrid 300 to arrive at current pixel p. Ray r may have a random sampletime and a random entry point 1106 into voxel grid 300.

At operation 1210, ray marching is performed for current ray r. Forexample, the value of a parameter may be obtained for each voxel alongthe path ray r takes through voxel grid 300 at the time associated withray r at the time associated with time r. In some embodiments, the valueof multiple parameters may be obtained for each voxel along the ray. Thevalue of a parameter associated with a voxel along ray r at time t canbe obtained from the voxel array 502 that is stored in association withthe voxel in temporal voxel buffer 500. The values of a parameter alonga ray may combined. For example, the values along the ray may beaveraged, or may be composited, e.g. by applying a rendering algorithmto the parameter values along the ray.

At operation 1212, it is determined whether ray marching has beenperformed for all N rays, i.e., it is determined whether current rayvalue r is less than N. If ray marching has not been performed for all Nrays, current ray value r is iterated, as indicated at operation 1214,so that ray marching may be performed for the next ray at operations1208-1210.

If ray marching has been performed for all N rays, the flow may proceedto operation 1216. In some embodiments, an average value across the Nrays can be determined from the composite values, as indicated atoperation 1216. As this average value depends on changes during a frame,the average value can capture effects of motion blur. The valuedetermined from ray marching at operations 1208-1216 may be stored inassociation with pixel p, as indicated at operation 1218.

At operation 1220, it is determined whether ray marching has beenperformed for all p pixels. If ray marching has not been performed forpixels, current pixel value p is iterated, as indicated at operation1222, so that ray marching may be performed for N rays at the next pixelat operations 1206-1218. If ray marching has been performed for allpixels, the flow ends, as indicated at 1224.

When pixel values have been assigned for all of the pixels of an image,a frame of an animated scene has been rendered.

V. System

FIG. 13 is a simplified block diagram of system 1300 for creatingcomputer graphics imagery (CGI) and computer-aided animation that mayimplement or incorporate various embodiments. In this example, system1300 can include one or more design computers 1310, one or more objectlibraries 1320, one or more object modeling systems 1330, one or moreobject articulation systems 1340, one or more object animation systems1350, one or more object simulation systems 1360, and one or more objectrendering systems 1370. Any of the systems 1330-1370 may be invoked byor used directly by a user of the one or more design computers 1310and/or automatically invoked by or used by one or more processesassociated with the one or more design computers 1310. Any of theelements of system 1300 can include hardware and/or software elementsconfigured for specific functions.

The one or more design computers 1310 can include hardware and softwareelements configured for designing CGI and assisting with computer-aidedanimation. Each of the one or more design computers 1310 may be embodiedas a single computing device or a set of one or more computing devices.Some examples of computing devices are PCs, laptops, workstations,mainframes, cluster computing system, grid computing systems, cloudcomputing systems, embedded devices, computer graphics devices, gamingdevices and consoles, consumer electronic devices having programmableprocessors, or the like. The one or more design computers 1310 may beused at various stages of a production process (e.g., pre-production,designing, creating, editing, simulating, animating, rendering,post-production, etc.) to produce images, image sequences, motionpictures, video, audio, or associated effects related to CGI andanimation.

In one example, a user of the one or more design computers 110 acting asa modeler may employ one or more systems or tools to design, create, ormodify objects within a computer-generated scene. The modeler may usemodeling software to sculpt and refine a neutral 3D model to fitpredefined aesthetic needs of one or more character designers. Themodeler may design and maintain a modeling topology conducive to astoryboarded range of deformations. In another example, a user of theone or more design computers 1310 acting as an articulator may employone or more systems or tools to design, create, or modify controls oranimation variables (avars) of models. In general, rigging is a processof giving an object, such as a character model, controls for movement,therein “articulating” its ranges of motion. The articulator may workclosely with one or more animators in rig building to provide and refinean articulation of the full range of expressions and body movementneeded to support a character's acting range in an animation. In afurther example, a user of design computer 1310 acting as an animatormay employ one or more systems or tools to specify motion and positionof one or more objects over time to produce an animation.

Object library 1320 can include elements configured for storing andaccessing information related to objects used by the one or more designcomputers 1310 during the various stages of a production process toproduce CGI and animation. Some examples of object library 1320 caninclude a file, a database, or other storage devices and mechanisms.Object library 1320 may be locally accessible to the one or more designcomputers 1310 or hosted by one or more external computer systems.

Some examples of information stored in object library 1320 can includean object itself, metadata, object geometry, object topology, rigging,control data, animation data, animation cues, simulation data, texturedata, lighting data, shader code, or the like. An object stored inobject library 120 can include any entity that has an n-dimensional(e.g., 2D or 3D) surface geometry. The shape of the object can include aset of points or locations in space (e.g., object space) that make upthe object's surface. Topology of an object can include the connectivityof the surface of the object (e.g., the genus or number of holes in anobject) or the vertex/edge/face connectivity of an object.

The one or more object modeling systems 1330 can include hardware and/orsoftware elements configured for modeling one or more objects. Modelingcan include the creating, sculpting, and editing of an object. Invarious embodiments, the one or more object modeling systems 1330 may beconfigured to generated a model to include a description of the shape ofan object. The one or more object modeling systems 1330 can beconfigured to facilitate the creation and/or editing of features, suchas non-uniform rational B-splines or NURBS, polygons and subdivisionsurfaces (or SubDivs), that may be used to describe the shape of anobject. In general, polygons are a widely used model medium due to theirrelative stability and functionality. Polygons can also act as thebridge between NURBS and SubDivs. NURBS are used mainly for theirready-smooth appearance and generally respond well to deformations.SubDivs are a combination of both NURBS and polygons representing asmooth surface via the specification of a coarser piecewise linearpolygon mesh. A single object may have several different models thatdescribe its shape.

The one or more object modeling systems 1330 may further generate modeldata (e.g., 2D and 3D model data) for use by other elements of system1300 or that can be stored in object library 1320. The one or moreobject modeling systems 1330 may be configured to allow a user toassociate additional information, metadata, color, lighting, rigging,controls, or the like, with all or a portion of the generated modeldata.

The one or more object articulation systems 1340 can include hardwareand/or software elements configured to articulating one or morecomputer-generated objects. Articulation can include the building orcreation of rigs, the rigging of an object, and the editing of rigging.In various embodiments, the one or more articulation systems 1340 can beconfigured to enable the specification of rigging for an object, such asfor internal skeletal structures or eternal features, and to define howinput motion deforms the object. One technique is called “skeletalanimation,” in which a character can be represented in at least twoparts: a surface representation used to draw the character (called theskin) and a hierarchical set of bones used for animation (called theskeleton).

The one or more object articulation systems 1340 may further generatearticulation data (e.g., data associated with controls or animationsvariables) for use by other elements of system 1300 or that can bestored in object library 1320. The one or more object articulationsystems 1340 may be configured to allow a user to associate additionalinformation, metadata, color, lighting, rigging, controls, or the like,with all or a portion of the generated articulation data.

The one or more object animation systems 1350 can include hardwareand/or software elements configured for animating one or morecomputer-generated objects. Animation can include the specification ofmotion and position of an object over time. The one or more objectanimation systems 1350 may be invoked by or used directly by a user ofthe one or more design computers 1310 and/or automatically invoked by orused by one or more processes associated with the one or more designcomputers 1310.

In various embodiments, the one or more animation systems 1350 may beconfigured to enable users to manipulate controls or animation variablesor utilized character rigging to specify one or more key frames ofanimation sequence. The one or more animation systems 1350 generateintermediary frames based on the one or more key frames. In someembodiments, the one or more animation systems 1350 may be configured toenable users to specify animation cues, paths, or the like according toone or more predefined sequences. The one or more animation systems 1350generate frames of the animation based on the animation cues or paths.In further embodiments, the one or more animation systems 1350 may beconfigured to enable users to define animations using one or moreanimation languages, morphs, deformations, or the like.

The one or more object animations systems 1350 may further generateanimation data (e.g., inputs associated with controls or animationsvariables) for use by other elements of system 1300 or that can bestored in object library 1320. The one or more object animations systems1350 may be configured to allow a user to associate additionalinformation, metadata, color, lighting, rigging, controls, or the like,with all or a portion of the generated animation data.

The one or more object simulation systems 160 can include hardwareand/or software elements configured for simulating one or morecomputer-generated objects. Simulation can include determining motionand position of an object over time in response to one or more simulatedforces or conditions. The one or more object simulation systems 1360 maybe invoked by or used directly by a user of the one or more designcomputers 1310 and/or automatically invoked by or used by one or moreprocesses associated with the one or more design computers 1310.

In various embodiments, the one or more object simulation systems 1360may be configured to enables users to create, define, or edit simulationengines, such as a physics engine or physics processing unit (PPU/GPGPU)using one or more physically-based numerical techniques. In general, aphysics engine can include a computer program that simulates one or morephysics models (e.g., a Newtonian physics model), using variables suchas mass, velocity, friction, wind resistance, or the like. The physicsengine may simulate and predict effects under different conditions thatwould approximate what happens to an object according to the physicsmodel. The one or more object simulation systems 1360 may be used tosimulate the behavior of objects, such as hair, fur, and cloth, inresponse to a physics model and/or animation of one or more charactersand objects within a computer-generated scene.

The one or more object simulation systems 1360 may further generatesimulation data (e.g., motion and position of an object over time) foruse by other elements of system 100 or that can be stored in objectlibrary 1320. The generated simulation data may be combined with or usedin addition to animation data generated by the one or more objectanimation systems 150. The one or more object simulation systems 1360may be configured to allow a user to associate additional information,metadata, color, lighting, rigging, controls, or the like, with all or aportion of the generated simulation data.

The one or more object rendering systems 1370 can include hardwareand/or software element configured for “rendering” or generating one ormore images of one or more computer-generated objects. “Rendering” caninclude generating an image from a model based on information such asgeometry, viewpoint, texture, lighting, and shading information. The oneor more object rendering systems 1370 may be invoked by or used directlyby a user of the one or more design computers 1310 and/or automaticallyinvoked by or used by one or more processes associated with the one ormore design computers 1310. One example of a software program embodiedas the one or more object rendering systems 1370 can includePhotoRealistic RenderMan, or PRMan, produced by Pixar Animations Studiosof Emeryville, Calif.

In various embodiments, the one or more object rendering systems 1370can be configured to render one or more objects to produce one or morecomputer-generated images or a set of images over time that provide ananimation. The one or more object rendering systems 1370 may generatedigital images or raster graphics images.

In various embodiments, a rendered image can be understood in terms of anumber of visible features. Some examples of visible features that maybe considered by the one or more object rendering systems 1370 mayinclude shading (e.g., techniques relating to how the color andbrightness of a surface varies with lighting), texture-mapping (e.g.,techniques relating to applying detail information to surfaces orobjects using maps), bump-mapping (e.g., techniques relating tosimulating small-scale bumpiness on surfaces), fogging/participatingmedium (e.g., techniques relating to how light dims when passing throughnon-clear atmosphere or air) shadows (e.g., techniques relating toeffects of obstructing light), soft shadows (e.g., techniques relatingto varying darkness caused by partially obscured light sources),reflection (e.g., techniques relating to mirror-like or highly glossyreflection), transparency or opacity (e.g., techniques relating to sharptransmissions of light through solid objects), translucency (e.g.,techniques relating to highly scattered transmissions of light throughsolid objects), refraction (e.g., techniques relating to bending oflight associated with transparency), diffraction (e.g., techniquesrelating to bending, spreading and interference of light passing by anobject or aperture that disrupts the ray), indirect illumination (e.g.,techniques relating to surfaces illuminated by light reflected off othersurfaces, rather than directly from a light source, also known as globalillumination), caustics (e.g., a form of indirect illumination withtechniques relating to reflections of light off a shiny object, orfocusing of light through a transparent object, to produce brighthighlights on another object), depth of field (e.g., techniques relatingto how objects appear blurry or out of focus when too far in front of orbehind the object in focus), motion blur (e.g., techniques relating tohow objects appear blurry due to high-speed motion, or the motion of thecamera), non-photorealistic rendering (e.g., techniques relating torendering of scenes in an artistic style, intended to look like apainting or drawing), or the like.

The one or more object rendering systems 1370 may further render images(e.g., motion and position of an object over time) for use by otherelements of system 1300 or that can be stored in object library 1320.The one or more object rendering systems 1370 may be configured to allowa user to associate additional information or metadata with all or aportion of the rendered image.

FIG. 14 is a block diagram of computer system 1400. FIG. 14 is merelyillustrative. In some embodiments, a computer system includes a singlecomputer apparatus, where the subsystems can be the components of thecomputer apparatus. In other embodiments, a computer system can includemultiple computer apparatuses, each being a subsystem, with internalcomponents. Computer system 1400 and any of its components or subsystemscan include hardware and/or software elements configured for performingmethods described herein.

Computer system 1400 may include familiar computer components, such asone or more one or more data processors or central processing units(CPUs) 1405, one or more graphics processors or graphical processingunits (GPUs) 1410, memory subsystem 1415, storage subsystem 1420, one ormore input/output (I/O) interfaces 1425, communications interface 1430,or the like. Computer system 1400 can include system bus 1435interconnecting the above components and providing functionality, suchconnectivity and inter-device communication.

The one or more data processors or central processing units (CPUs) 1405can execute logic or program code or for providing application-specificfunctionality. Some examples of CPU(s) 1405 can include one or moremicroprocessors (e.g., single core and multi-core) or micro-controllers,one or more field-gate programmable arrays (FPGAs), andapplication-specific integrated circuits (ASICs). As user herein, aprocessor includes a multi-core processor on a same integrated chip, ormultiple processing units on a single circuit board or networked.

The one or more graphics processor or graphical processing units (GPUs)1410 can execute logic or program code associated with graphics or forproviding graphics-specific functionality. GPUs 1410 may include anyconventional graphics processing unit, such as those provided byconventional video cards. In various embodiments, GPUs 1410 may includeone or more vector or parallel processing units. These GPUs may be userprogrammable, and include hardware elements for encoding/decodingspecific types of data (e.g., video data) or for accelerating 2D or 3Ddrawing operations, texturing operations, shading operations, or thelike. The one or more graphics processors or graphical processing units(GPUs) 1410 may include any number of registers, logic units, arithmeticunits, caches, memory interfaces, or the like.

Memory subsystem 1415 can store information, e.g., usingmachine-readable articles, information storage devices, orcomputer-readable storage media. Some examples can include random accessmemories (RAM), read-only-memories (ROMS), volatile memories,non-volatile memories, and other semiconductor memories. Memorysubsystem 1415 can include data and program code 1440.

Storage subsystem 1420 can also store information using machine-readablearticles, information storage devices, or computer-readable storagemedia. Storage subsystem 1420 may store information using storage media1445. Some examples of storage media 1445 used by storage subsystem 1420can include floppy disks, hard disks, optical storage media such asCD-ROMS, DVDs and bar codes, removable storage devices, networkedstorage devices, or the like. In some embodiments, all or part of dataand program code 1440 may be stored using storage sub system 1420.

The one or more input/output (I/O) interfaces 1425 can perform I/Ooperations. One or more input devices 1450 and/or one or more outputdevices 1455 may be communicatively coupled to the one or more I/Ointerfaces 1425. The one or more input devices 1450 can receiveinformation from one or more sources for computer system 1400. Someexamples of the one or more input devices 1450 may include a computermouse, a trackball, a track pad, a joystick, a wireless remote, adrawing tablet, a voice command system, an eye tracking system, externalstorage systems, a monitor appropriately configured as a touch screen, acommunications interface appropriately configured as a transceiver, orthe like. In various embodiments, the one or more input devices 1450 mayallow a user of computer system 1400 to interact with one or morenon-graphical or graphical user interfaces to enter a comment, selectobjects, icons, text, user interface widgets, or other user interfaceelements that appear on a monitor/display device via a command, a clickof a button, or the like.

The one or more output devices 1455 can output information to one ormore destinations for computer system 1400. Some examples of the one ormore output devices 1455 can include a printer, a fax, a feedback devicefor a mouse or joystick, external storage systems, a monitor or otherdisplay device, a communications interface appropriately configured as atransceiver, or the like. The one or more output devices 1455 may allowa user of computer system 1400 to view objects, icons, text, userinterface widgets, or other user interface elements. A display device ormonitor may be used with computer system 1400 and can include hardwareand/or software elements configured for displaying information.

Communications interface 1430 can perform communications operations,including sending and obtaining data. Some examples of communicationsinterface 1430 may include a network communications interface (e.g.Ethernet, Wi-Fi, etc.). For example, communications interface 1430 maybe coupled to communications network/external bus 1460, such as acomputer network, a USB hub, or the like. A computer system can includea plurality of the same components or subsystems, e.g., connectedtogether by communications interface 1430 or by an internal interface.In some embodiments, computer systems, subsystem, or apparatuses cancommunicate over a network. In such instances, one computer can beconsidered a client and another computer a server, where each can bepart of a same computer system. A client and a server can each includemultiple systems, subsystems, or components.

Computer system 1400 may also include one or more applications (e.g.,software components or functions) to be executed by a processor toexecute, perform, or otherwise implement techniques disclosed herein.These applications may be embodied as data and program code 1440.Additionally, computer programs, executable computer code,human-readable source code, shader code, rendering engines, or the like,and data, such as image files, models including geometrical descriptionsof objects, ordered geometric descriptions of objects, proceduraldescriptions of models, scene descriptor files, or the like, may bestored in memory subsystem 1415 and/or storage subsystem 1420.

Such programs may also be encoded and transmitted using carrier signalsadapted for transmission via wired, optical, and/or wireless networksconforming to a variety of protocols, including the Internet. As such, acomputer readable medium according to an embodiment may be created usinga data signal encoded with such programs. Computer readable mediaencoded with the program code may be packaged with a compatible deviceor provided separately from other devices (e.g., via Internet download).Any such computer readable medium may reside on or within a singlecomputer product (e.g. a hard drive, a CD, or an entire computersystem), and may be present on or within different computer productswithin a system or network. A computer system may include a monitor,printer, or other suitable display for providing any of the resultsmentioned herein to a user.

Any of the methods described herein may be totally or partiallyperformed with a computer system including one or more processors, whichcan be configured to perform the steps. Thus, embodiments can bedirected to computer systems configured to perform the steps of any ofthe methods described herein, potentially with different componentsperforming a respective steps or a respective group of steps. Althoughpresented as numbered steps, steps of methods herein can be performed ata same time or in a different order. Additionally, portions of thesesteps may be used with portions of other steps from other methods. Also,all or portions of a step may be optional. Additionally, any of thesteps of any of the methods can be performed with modules, circuits, orother means for performing these steps.

The specific details of particular embodiments may be combined in anysuitable manner without departing from the spirit and scope ofembodiments. However, other embodiments may be directed to specificembodiments relating to each individual aspect, or specific combinationsof these individual aspects.

The above description of exemplary embodiments has been presented forthe purposes of illustration and description. It is not intended to beexhaustive or to limit the invention to the precise form described, andmany modifications and variations are possible in light of the teachingabove. The embodiments were chosen and described in order to bestexplain the principles and its practical applications to thereby enableothers skilled in the art to best utilize the invention in variousembodiments and with various modifications as are suited to theparticular use contemplated.

A recitation of “a”, “an” or “the” is intended to mean “one or more”unless specifically indicated to the contrary.

All patents, patent applications, publications, and descriptionsmentioned here are incorporated by reference in their entirety for allpurposes. None is admitted to be prior art.

What is claimed is:
 1. A computer-implemented method comprising:storing, by a processor in a memory, a first voxel array associated witha first voxel in a voxel grid that covers at least a portion of athree-dimensional model, wherein the first voxel array includes: aplurality of time values, and for each of the plurality of time values,a parameter value of a parameter of an animated scene associated withthe first voxel at the time value; storing, by the processor in thememory, a second voxel array associated with a second voxel in the voxelgrid, wherein the second voxel array includes: at least one time value,and for each of the at least one time value, a parameter value of theparameter of the animated scene associated with the second voxel at thetime value, wherein at least one of the plurality of time valuesincluded in the first voxel array is different from each of the at leastone time value included in the second voxel array; determining, by theprocessor, using the first voxel array, a first parameter value of theparameter of the animated scene associated with the first voxel at afirst time value; determining, by the processor, using the second voxelarray, a second parameter value of the parameter of the animated sceneassociated with the second voxel at a second time value; and rendering,by the processor, the animated scene using the first and secondparameter values.
 2. The computer-implemented method of claim 1, whereina number of time values in the second voxel array is fewer than a numberof time values in the first voxel array.
 3. The computer-implementedmethod of claim 1, wherein a distribution of the plurality of timevalues included in the first voxel array is different from adistribution of the at least one time value included in the second voxelarray.
 4. The computer-implemented method of claim 1, wherein theparameter values for each time value of the first voxel array aresampled at a plurality of positions within the first voxel.
 5. Thecomputer-implemented method of claim 4, wherein the plurality of timevalues are random and the plurality of positions within the voxel arerandom.
 6. The computer-implemented method of claim 1, wherein theparameter values stored in a voxel array are generated from sampling atleast one parameter value associated with a microvoxel lattice vertex.7. The computer-implemented method of claim 1, wherein a parameter valueat a first time value is determined by sampling at least two parametervalues of a fluid simulation field, wherein a first parameter value of afluid simulation field is sampled at an increased time value that isgreater than the first time value and a second parameter value of afluid simulation field is sampled at a decreased time value that is lessthan the second time value, and wherein an advection algorithm is usedto determine the first time value based on the increased time value andthe decreased time value.
 8. The computer-implemented method of claim 1,wherein the parameter is density.
 9. The computer-implemented method ofclaim 1, wherein a plurality of parameter values are stored for eachtime value of the first voxel array and the second voxel array.
 10. Thecomputer-implemented method of claim 9, wherein the plurality ofparameters include at least one of density, color, opacity, temperature,and attenuation coefficient.
 11. The computer-implemented method ofclaim 1, further comprising compressing data of the second voxel arraysuch that the number of time values in the second array is fewer thanthe number of time values in the first array.
 12. Thecomputer-implemented method of claim 11, wherein compressing the data ofthe second voxel array includes removing at least one redundant valuefrom the data of the second voxel array.
 13. The computer-implementedmethod of claim 11, wherein compressing the data of the second voxelarray includes applying a lossy compression algorithm to the data of thesecond voxel array.
 14. The computer-implemented method of claim 1,further comprising storing an first offset value for the first voxel andstoring a second offset value for the second voxel, wherein the firstoffset value indicates the location in a table of a first sample valuefor the first voxel and wherein the second offset value indicates thelocation in the table of a first sample value for the second voxel. 15.The computer-implemented method of claim 1, wherein the voxel grid has afixed position in the animated scene over the plurality of time valuesincluded in the first voxel array.
 16. The computer-implemented methodof claim 1, wherein determining, using the second voxel array, thesecond parameter value includes: selecting the second time value, thesecond time value being different from the at least time one valueincluded in the second voxel array; and determining the second parametervalue of the parameter of the animated scene associated with the secondvoxel at the second time value based on an interpolation using theparameter value of the parameter of the animated scene associated withthe second voxel at the at least one time value.
 17. A computer productcomprising a non-transitory computer readable medium storing a pluralityof instructions that when executed control a computer system to performcomputer-generated animation, the instructions comprising: storing afirst voxel array associated with a first voxel in a voxel grid thatcovers at least a portion of a three-dimensional model, wherein thefirst voxel array includes: a plurality of time values, and for each ofthe plurality of time values, a parameter value of a parameter of ananimated scene in the first voxel at the time value; storing a secondvoxel array associated with a second voxel in the voxel grid, whereinthe second voxel array includes: at least one time value, for each ofthe at least one time value, a parameter value the parameter of theanimated scene associated with the second voxel at the time value,wherein at least one of the plurality of time values included in thefirst voxel array is different from each of the at least one time valueincluded in the second voxel array; determining, using the first voxelarray, a first parameter value of the parameter of the animated sceneassociated with the first voxel at a first time value; determining,using the second voxel array, a second parameter value of the parameterof the animated scene associated with the second voxel at a second timevalue; and rendering the animated scene using the first and secondparameter values.
 18. The computer product of claim 17, wherein a numberof time values in the second voxel array is fewer than a number of timevalues in the first voxel array.
 19. The computer product of claim 17,wherein a distribution of the plurality of time values included in thefirst voxel array is different from a distribution of the at least onetime value included in the second voxel array.
 20. The computer productof claim 17, wherein the parameter values for each time value of thefirst voxel array are sampled at a plurality of positions within thefirst voxel.
 21. The computer product of claim 20, wherein the pluralityof time values are random and the plurality of positions within thevoxel are random.
 22. The computer product of claim 17, wherein theparameter values stored in a voxel array are generated from sampling atleast one parameter value associated with a microvoxel lattice vertex.23. The computer product of claim 17, wherein a parameter value at afirst time value is determined by sampling at least two parameter valuesof a fluid simulation field, wherein a first parameter value of a fluidsimulation field is sampled at an increased time value that is greaterthan the first time value and a second parameter value of a fluidsimulation field is sampled at a decreased time value that is less thanthe second time value, and wherein an advection algorithm is used todetermine the first time value based on the increased time value and thedecreased time value.
 24. The computer product of claim 17, wherein theparameter is density.
 25. The computer product of claim 17, wherein aplurality of parameter values are stored for each time value of thefirst voxel array and the second voxel array.
 26. The computer productof claim 25, wherein the plurality of parameters include at least one ofdensity, color, opacity, temperature, and attenuation coefficient. 27.The computer product of claim 17, further comprising compressing data ofthe second voxel array such that the number of time values in the secondarray is fewer than the number of time values in the first array. 28.The computer product of claim 27, wherein compressing the data of thesecond voxel array includes removing at least one redundant value fromthe data of the second voxel array.
 29. The computer product of claim27, wherein compressing the data of the second voxel array includesapplying a lossy compression algorithm to the data of the second voxelarray.
 30. The computer product of claim 17, further comprising storingan first offset value for the first voxel and storing a second offsetvalue for the second voxel, wherein the first offset value indicates thelocation in a table of a first sample value for the first voxel andwherein the second offset value indicates the location in the table of afirst sample value for the second voxel.
 31. The computer product ofclaim 2, wherein determining, using the second voxel array, the secondparameter value includes: selecting the second time value, the secondtime value being different from the at least time one value included inthe second voxel array; and determining the second parameter value ofthe parameter of the animated scene associated with the second voxel atthe second time value based on an interpolation using the parametervalue of the parameter of the animated scene associated with the secondvoxel at the at least one time value.